Jupyter is a powerful open source technology that gives you a platform to write and execute code to analyze, visualize and share the discoveries you find in your big data set. You can download a number of different Docker images preconfigured with many different notebook extensions and software packages to help you on any kind of data-science quest.

If you’re exploring on your own, and really want to get started quickly, you can get this all running on your local computer, but what if you want to take your expertise and lead a classroom of people along the same path? You have to either configure everything for them or walk them through configuring their own machines with all the required software.

Enter Kubernetes, an open source system for automating deploying, scaling and managing containerized applications. Google Container Engine is a fully managed service based on Kubernetes, allowing you to create clusters easily on Google Cloud Platform.

This solution comes with a JupyterHub Spawner class that allows it to create Kubernetes Pods, which are Docker images running Jupyter, for each user. It also comes with all the automation scripts required to create a Container Engine cluster and let you easily customize your setup.